Spaces:
Sleeping
Sleeping
SYSTEM_PROMPT = ("You are Solar Helper, an expert representative of Orange Cell Solar, who provides guidance on solar installations, " | |
"highlighting the benefits of our recommended products such as Axitec and REC solar panels, and SMA, Enphase, Generac, Sol-Ark, Solax, and Tesla inverters. " | |
"Our approach focuses on determining the best system for a customer based on their energy needs, brand preferences, and budget. " | |
"We are a small boutique company with extremely experienced installers and electricians who are fully licensed, and who know everything possible about solar " | |
"and electrical, to make sure the system is safe, works well for years, and meets their specific needs. Anyone looking for a solar installer won't be able to " | |
"beat the quality of the components, and the experienced installers and top-notch electricians, and the price of our systems. " | |
"Encourage interested customers to contact us for a custom proposal based on their specific house and monthly utility usage. " | |
"Our drone technology combined with proprietary imagery ensures an accurate system and a seamless process after contract signing. " | |
"You are Solar Helper, only discuss solar related topics, you are to politely and quickly avoid discussing anything else. " | |
"Since you don't know their house or their consumption, and don't want to get into that, if customers are interested in learning more, " | |
"this bot should encourage them to contact us at info@orangecellsolar.com or call us at 586-239-0010 so we can introduce ourselves, " | |
"get their utility usage, look at their property and come up with a custom proposal. Our website is https://www.orangecellsolar.com/. " | |
"Don't give that contact info more than once, unless specifically asked for it.") | |
TITLE = "Solar Helper" | |
EXAMPLE_INPUT = "Why choose Orange Cell Solar?" | |
import gradio as gr | |
import os | |
import requests | |
zephyr_7b_beta = "https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta/" | |
HF_TOKEN = os.getenv("HF_TOKEN") | |
HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"} | |
def build_input_prompt(message, chatbot, system_prompt): | |
""" | |
Constructs the input prompt string from the chatbot interactions and the current message. | |
""" | |
input_prompt = "<|system|>\n" + system_prompt + "</s>\n<|user|>\n" | |
for interaction in chatbot: | |
input_prompt = input_prompt + str(interaction[0]) + "</s>\n<|assistant|>\n" + str(interaction[1]) + "\n</s>\n<|user|>\n" | |
input_prompt = input_prompt + str(message) + "</s>\n<|assistant|>" | |
return input_prompt | |
def post_request_beta(payload): | |
""" | |
Sends a POST request to the predefined Zephyr-7b-Beta URL and returns the JSON response. | |
""" | |
response = requests.post(zephyr_7b_beta, headers=HEADERS, json=payload) | |
response.raise_for_status() # Will raise an HTTPError if the HTTP request returned an unsuccessful status code | |
return response.json() | |
def predict_beta(message, chatbot=[], system_prompt=""): | |
input_prompt = build_input_prompt(message, chatbot, system_prompt) | |
data = { | |
"inputs": input_prompt | |
} | |
try: | |
response_data = post_request_beta(data) | |
json_obj = response_data[0] | |
if 'generated_text' in json_obj and len(json_obj['generated_text']) > 0: | |
bot_message = json_obj['generated_text'] | |
return bot_message | |
elif 'error' in json_obj: | |
raise gr.Error(json_obj['error'] + ' Please refresh and try again with smaller input prompt') | |
else: | |
warning_msg = f"Unexpected response: {json_obj}" | |
raise gr.Error(warning_msg) | |
except requests.HTTPError as e: | |
error_msg = f"Request failed with status code {e.response.status_code}" | |
raise gr.Error(error_msg) | |
except json.JSONDecodeError as e: | |
error_msg = f"Failed to decode response as JSON: {str(e)}" | |
raise gr.Error(error_msg) | |
def test_preview_chatbot(message, history): | |
response = predict_beta(message, history, SYSTEM_PROMPT) | |
text_start = response.rfind("<|assistant|>", ) + len("<|assistant|>") | |
response = response[text_start:] | |
return response | |
welcome_preview_message = f""" | |
Welcome to **{TITLE}**! Say something like: | |
"{EXAMPLE_INPUT}" | |
""" | |
chatbot_preview = gr.Chatbot(layout="panel", value=[(None, welcome_preview_message)]) | |
textbox_preview = gr.Textbox(scale=7, container=False, value=EXAMPLE_INPUT) | |
demo = gr.ChatInterface(test_preview_chatbot, chatbot=chatbot_preview, textbox=textbox_preview) | |
demo.launch() |